Pedro Liliana, Rudewicz Patrick J
Novartis Institutes for BioMedical Research, Emeryville, California 94608, United States.
Anal Chem. 2020 Dec 15;92(24):16005-16015. doi: 10.1021/acs.analchem.0c03534. Epub 2020 Dec 6.
The analysis of large numbers of cells from a population results in information that does not reflect differences in cell phenotypes. Individual variations in cellular drug uptake, metabolism, and response to drug treatment may have profound effects on cellular survival and lead to the development of certain disease states, drug persistence, and resistance. Herein, we present a method that combines live cell confocal microscopy imaging with high-resolution mass spectrometry to achieve absolute cell quantification of the drug amiodarone (AMIO) and its major metabolite, -desethylamiodarone (NDEA), in single liver cells (HepG2 and HepaRG cells). The method uses a prototype system that integrates a confocal microscope with an XYZ stage robot to image and automatically sample selected cells from a sample compartment, which is kept under growth conditions, with nanospray tips. Besides obtaining the distributions of AMIO and NDEA cell concentrations across a population of individual cells, as well as variabilities in drug metabolism, the effect of these on phospholipidosis and cell morphology was studied. The method was suited to identify subpopulations of cells that metabolized less drug and to correlate cell drug concentrations with cell phospholipid content, cell volume, sphericity, and other cell phenotypic features. Using principal component analysis (PCA), the treated cells could be clearly distinguished from vehicle control cells (0 μM AMIO) and HepaRG cells from HepG2 cells. The potential of using multidimensional and multimodal information collected from single cells to build predictive models for cell classification is demonstrated.
对群体中大量细胞进行分析所得到的信息并不能反映细胞表型的差异。细胞对药物摄取、代谢以及对药物治疗反应的个体差异可能会对细胞存活产生深远影响,并导致某些疾病状态、药物持续性和耐药性的发展。在此,我们提出一种方法,该方法将活细胞共聚焦显微镜成像与高分辨率质谱相结合,以实现对单个肝细胞(HepG2和HepaRG细胞)中药物胺碘酮(AMIO)及其主要代谢产物去乙基胺碘酮(NDEA)的绝对细胞定量。该方法使用一个原型系统,该系统将共聚焦显微镜与XYZ平台机器人集成在一起,以便用纳米喷雾尖端对来自保持在生长条件下的样品隔室中的选定细胞进行成像并自动取样。除了获得AMIO和NDEA细胞浓度在单个细胞群体中的分布以及药物代谢的变异性之外,还研究了这些对磷脂沉积和细胞形态的影响。该方法适用于识别药物代谢较少的细胞亚群,并将细胞药物浓度与细胞磷脂含量、细胞体积、球形度和其他细胞表型特征相关联。使用主成分分析(PCA),可以将处理过的细胞与溶剂对照细胞(0μM AMIO)清楚地区分开来,并将HepaRG细胞与HepG2细胞区分开来。展示了利用从单细胞收集的多维和多模态信息构建细胞分类预测模型的潜力。